Please use this identifier to cite or link to this item: https://etd.cput.ac.za/handle/20.500.11838/4054
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dc.contributor.advisorKriger, Carlen_US
dc.contributor.authorNdlovu, Musawenkosien_US
dc.date.accessioned2024-04-29T08:08:33Z-
dc.date.available2024-04-29T08:08:33Z-
dc.date.issued2024-
dc.identifier.urihttps://etd.cput.ac.za/handle/20.500.11838/4054-
dc.descriptionThesis (MEng (Electrical Engineering))--Cape Peninsula University of Technology, 2024en_US
dc.description.abstractThe problem of environmental pollution resulting from sewage spillage is a significant concern in South Africa, a country with aging infrastructure. Municipalities, particularly local municipalities located in rural and semi-rural areas, are tasked with the collection and treatment of household sewage. Manual monitoring methods currently in use are labour-intensive, prone to inaccuracies, and lack real-time data capabilities. This study investigates the feasibility of deploying intelligent monitoring technology to address sewage-related pollution issues. The proposed intelligence involves the utilization of sensors capable of real-time data collection and feedback, aimed at preventing sewage spillage and addressing it promptly. The research is conducted within a local municipality in semi-rural South Africa, serving as a worst-case scenario with findings applicable to more developed regions within the country. The envisioned system leverages advanced technologies and adheres to IEEE standards such as IEEE 1451 for sensor interoperability and IEEE 802.11 for wireless communication. Its primary objectives are real-time monitoring, early pollution detection, and rapid intervention to prevent sewage spillage. A comprehensive literature review highlights the shortcomings of manual sewage monitoring and explores the potential of smart sensors and data-driven solutions in mitigating sewage pollution. The research involves the development of monitoring models and data analytics using MATLAB, with a specific focus on the pump station and sump section of the sewer network. The implementation of this smart sensor and data-driven sewage monitoring system enhances resource allocation efficiency, enables targeted maintenance, and ensures timely responses. The integration of electrical and automation technologies further enhances the reliability, accuracy, and scalability of sewage monitoring operations. The study's findings contribute to the formulation of effective pollution management strategies, inform policy-making decisions, and provide guidance for the implementation of smart monitoring systems in municipalities. These outcomes contribute to sustainable development efforts and a cleaner, healthier environment in South Africa, offering a transferable solution applicable to regions worldwide facing similar challenges.en_US
dc.language.isoenen_US
dc.publisherCape Peninsula University of Technologyen_US
dc.subjectEnvironmental pollutionen_US
dc.subjectSewage -- Environmental aspectsen_US
dc.subjectSewage disposalen_US
dc.subjectSewerage -- Maintenance and repairen_US
dc.subjectSewage disposal plantsen_US
dc.subjectSewage -- Purificationen_US
dc.subjectEnvironmental protectionen_US
dc.subjectEnvironmental protectionen_US
dc.subjectSmart sensorsen_US
dc.subjectReal-time monitoringen_US
dc.subjectIEEE standardsen_US
dc.subjectNdlambe Local Municipalityen_US
dc.titleSmart monitoring of sewage infrastructure to alleviate environmental pollutionen_US
dc.typeThesisen_US
dc.identifier.doihttps://doi.org/10.25381/cput.25225124.v1-
Appears in Collections:Electrical, Electronic and Computer Engineering - Master's Degree
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